Platform bans cannot prevent rivals from distilling superior model outputs to train their own.
Lagging AI developers quietly bypass platform bans to train their models on the outputs of superior competitors while claiming independent technology.
The same conclusion keeps arriving from across the workspace's research — 1 topics independently instantiate this theme. Filter the evidence by where it came from:
Elon Musk's xAI secretly circumvented safety guidelines to train its own developer models using outputs distilled from superior rival Claude.
Hosting a competitor's workloads on adjacent hardware provides operational visibility that helps the landlord study and run the competitor's high-value model patterns.
It presents high-profile political and corporate friction stemming from accusations that lagging labs train their competitive models on distilled outputs of superior U.S. systems.
It highlights how developers quietly worked around platform lockouts to continue distilling data from a superior competitor's models.
Developers leverage API access to superior competitors to distill outputs and train their own models, bypassing standard platform constraints.
Despite platform bans, Chinese developers bypass restrictions by using OpenAI's API outputs to distill knowledge and train their own models.
Allegations that Z.ai's near-frontier GLM-5.2 was trained by distilling outputs from Google and Anthropic models illustrate the futility of platform constraints in preventing model logic capture.